Prompt
What's the best speech-to-text API for transcribing noisy customer support calls with speaker diarization?
Latest observation
For noisy customer support calls with speaker diarization, the best choice depends on what you mean by “best”:
Best overall for call-center accuracy + diarization
AssemblyAI
- Strong transcription on messy, real-world audio
- Good speaker diarization
- Useful call-center features like sentiment, PII redaction, chapters, summaries
- Easy API and strong developer experience
Best for enterprise-scale + broad speech features
Google Cloud Speech-to-Text
- Very solid accuracy, especially if your audio is decent
- Supports speaker diarization
- Good for production workloads
- Strong global infrastructure and reliability
Best if you need strong customization / telephony workflows
Deepgram
- Often excellent on noisy, low-bandwidth, phone-style audio
- Supports diarization
- Fast, developer-friendly, good streaming support
- Frequently chosen for contact-center use cases
Best if you want flexibility and can self-host
OpenAI Whisper-based solutions
- Good general transcription quality
- But native diarization is not built in
- You’d need a separate diarization layer, which adds complexity
My practical recommendation
If your main use case is customer support calls, I’d start with:
- Deepgram if you care most about noisy phone audio and streaming
- AssemblyAI if you want a very strong out-of-the-box call analytics package
- Google Cloud STT if you already use GCP and want enterprise integration
What to look for specifically
For your case, prioritize:
- Robustness to phone audio / background noise
- Speaker diarization quality
- Streaming transcription latency
- Word-level timestamps
- Punctuation and formatting
- Call-center add-ons like sentiment, redaction, summarization
- Cost at scale
Short answer
If I had to pick one for noisy customer support calls with diarization, I’d say:
Deepgram for the best balance of noisy-audio performance and diarization,
with AssemblyAI as the best alternative if you want richer call analytics.
If you want, I can also give you a side-by-side comparison table of Deepgram vs AssemblyAI vs Google Cloud vs AWS vs OpenAI for this exact use case.
Observation history
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How did Obsurfable measure this prompt?
Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.
Which AI systems does Obsurfable collect answers from?
OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, and Meta AI.